Data Science has become an inevitable charter in our everyday lives where every action of ours is measured, plotted, classified and logged. We leave traces of who we are while diving a car, when visiting a place, after watching a movie or shopping what we want. These traces of data captured…

R for SQListas, part 2

Welcome to part 2 of my “R for SQListas” series. Last time, it was all about how to get started with R if you’re a SQL girl (or guy)- and that basically meant an introduction to Hadley Wickham’s dplyr and the tidyverse. The logic being: Don’t fear, it’s not that different from what…

Summary: This new study claims to be able to identify criminals based on their facial characteristics. Even if the data science is good has AI pushed too far into areas of societal taboos? This isn’t the first time data science has been restricted in favor of social goals, but this study may be a trip wire that starts a long and difficult discussion about the role of AI.

Has AI gone too far? This might seem like a nonsensical question to data…

With more and more people browsing online from smartphones and tablets, it's no longer a question of whether one needs a mobile application for their business or E-Commerce site, but rather how to get it developed.

There are a few different options available for your mobile app development project, depending on the budget, target demographic and other factors, all outlined below. In short, there are 4 main routes to…

This article was posted by Ryan Swanstrom on Data Science 101. Ryan is helping the world learn data science at Microsoft.

The differences between Data Scientists, Data Engineers, and Software engineers can get a little confusing at times. Thus, here is a guest post provided by Jake Stein, CEO at Stitch formerly RJ Metrics, which aims to clear up some of that confusion based upon LinkedIn data.

As data grows, so does the expertise needed to manage it. The past few years…

This post is 'not' intended to teach people how to use popular predictive modelling APIs for free. Although, to your surprise, this isn't a far fetched possibility. Trained Machine learning models are basically a function that maps feature vectors to the output variable. Upon querying with a test instance, the model predicts an outcome, assigning…

This is part of a new series of articles: once or twice a month, we post previous articles that were very popular when first published. These articles are at least 6 month old but no more than 12 month old. The previous digest in this series was posted here a while back.

Human behaviors, rituals & habits are the outcome of complex interplay of the environment and experiences they have been exposed to. These definitely play a big role in shaping our product interaction experience. All of us have intuitively understood the importance of "cognitive resonance" in the first 8 seconds we interact with a product and how that experience has subsequently shaped our outlook to our product. As…

While it is easy to find salary surveys for data scientists and related professions both at the junior and senior level, broken down per location and skills set, very few analyses show salary progress over the course of a 25 years career.…

Here I offer a few off-the-beaten-path interesting problems that you won't find in textbooks, data science camps, or in college classes. These problems range from applied maths, to statistics and computer science, and are aimed at getting the novice interested in a few core subjects that most data scientists master. The problems are described in simple English and don't require math / stats / probability knowledge beyond high school level. My goal is to attract people interested in data…

Guest blog by Sebastian Raschka. Sebastian Raschka is the author of the bestselling book “Python Machine Learning.” As a Ph.D. candidate at Michigan State University, he is developing new computational methods in the field of computational biology. Sebastian has many years of experience with coding in…

If you were to ask people whose work revolves around business technology, they would probably describe this as the Times of the Great Migration. The migration in question is the one from the traditional desktop business software solutions to those that are cloud-based or provided as a service.

Guest blog by James Kobielus. James is IBM's Big Data Evangelist. He is an industry veteran who spearheads IBM's thought leadership activities in big data, data science, enterprise data warehousing, advanced analytics, Hadoop, business intelligence, data management, and next best action technologies. Prior to joining IBM, he was a leading industry analyst, with firms including Forrester Research,…